Building an internal rating system conceptual framework
This presentation is the property of its rightful owner.
Sponsored Links
1 / 33

Building an Internal Rating System : Conceptual Framework PowerPoint PPT Presentation


  • 92 Views
  • Uploaded on
  • Presentation posted in: General

Building an Internal Rating System : Conceptual Framework. Michael Peng. Agenda. Key attributes of an Internal Rating System Expected Loss Framework Rating and PDs Exposure and Facility tracking Loss Given Default Case Study – Rating Management System Concluding Comments.

Download Presentation

Building an Internal Rating System : Conceptual Framework

An Image/Link below is provided (as is) to download presentation

Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author.While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server.


- - - - - - - - - - - - - - - - - - - - - - - - - - E N D - - - - - - - - - - - - - - - - - - - - - - - - - -

Presentation Transcript


Building an internal rating system conceptual framework

Building an Internal Rating System : Conceptual Framework

Michael Peng


Agenda

Agenda

Key attributes of an Internal Rating System

Expected Loss Framework

Rating and PDs

Exposure and Facility tracking

Loss Given Default

Case Study – Rating Management System

Concluding Comments


What is an internal rating system

What is an Internal Rating System ?

Credit Rating System consists of all of the methods, processes, controls and data collection and IT systems that support the assessment of credit risk, the assignment of internal risk ratings and the quantification of default and loss estimates.

Internal rating system is the prerequisite for advanced credit risk management, and each financial institution is expected to develop its own internal rating system. Every institution faces a different business environment, so each system should have its own design. For example, a more simple framework might be suitable for small institutions . There is no single answer for the framework of internal rating systems, such as the number of rating grades, a definition of each rating grade, and the method of rating assignments. Financial institutions need to introduce their own system depending on the characteristics of their loan portfolios, their operations, the objectives of the rating system, and other factors. Obviously, the institutions need to make necessary adjustments flexibly due to changes in the business environment.


How is ir related to basel ii

The New Basle Capital Accord – Consultative Document, April 2003

Appropriate rating system for each asset class

Multiple methodologies allowed within each asset class (large corporate , SME)

CORPORATE/ BANK/ SOVEREIGN EXPOSURES

RETAIL EXPOSURES

  • Two dimensional rating system

    • Risk of borrower default

  • Each borrower must be assigned a rating

    • Transaction specific factors (For banks using advanced approach, facility rating must exclusively reflect LGD)

  • Minimum of seven borrower grades for non-defaulted borrowers and one for those that have defaulted

  • Each retail exposure must be assigned to a particular pool

  • The pools should provide for meaningful

    differentiation of risk, grouping of sufficiently homogenous exposures and allow for accurate and consistent estimation of loss characteristics at pool level

How is IR related to Basel II?


Why building internal rating system 1

Why Building Internal Rating System (1)?

When banks build their internal rating system, their objective is twofold.

  • First they want to assess the creditworthiness of companies during the loan application process.

  • Second they want to use rating information to feed their portfolio management tools designed to produce regulatory capital or economic capital measures.


The use of internal rating system

The Use of Internal Rating System

  • Setting upper credit limits based on rating grades: For example, institutions can extend a smaller amount of loans to low-graded borrowers and thereby avoid the risk of credit concentration in them.

  • Setting authority ranks for loan approval by rating grade: For example, loan officers at bank branches can make loan decisions for only a limited amount of loans to low-graded borrowers.

  • Simplifying the loan review process for higher-graded borrowers: Risk-based allocation of risk management resources can improve efficiency of the overall loan review process.


Foundation irb vs advanced irb approach

Foundation IRB Vs Advanced IRB Approach


An overview of credit risk measurement under bis ii framework

Migration Matrix

Probability of Default (PD)

Portfolio Monitoring

Provisioning

Pricing

Profit Management

Capital Allocation

An Overview of credit risk measurement under BIS II Framework

Internal Rating System

Qualitative Evaluation

Internal Rating

Quantitative Evaluation

Reporting to the Board

Financial Data

Stress Testing

Loss Given Default

(LGD)

Risk Components

Calculation of Credit Risk Amount

Expected Loss (EL)

Unexpected Loss (UL)

Exposure at Default

(EAD)

Correlation

Quantification of Credit Risk

Internal Use

Source: BoJ Sep 2005


A simple look on pillar 1 irb tasks

A Simple Look on Pillar 1 IRB Tasks

Estimation of Risk Components

Architecture of an Internal Rating System,

Internal Use

Risk estimates (i.e., PD, LGD, EAD) predictive and accurate?

“Use Test”*: Pricing,

Portfolio Monitoring,

Credit Risk Quantification?

Quantitative Rating Model

Qualitative Evaluation

Validation Work

* Use Test: IRB provision that requires ratings and default and loss estimates to “play an essential role” in the Institution’s credit approval, risk management, internal capital allocations and corporate governance functions.

Source: BoJ Sep 2005


Building an internal rating system conceptual framework

Overview of a

Rating Management System

Audit Trail

Ratings summary

Facility/ Exposure details

Collateral and LGD details

Quantitative inputs

Qualitative inputs


Building an internal rating system conceptual framework

Internal ratings System (RMS):

User Interface

Bank’s own internal view

Rating Templates

Qualitative assessment

Quantitative Assessment

External Ratings

External Models

Peer comparison


Building an internal rating system conceptual framework

1. Key Attributes of an Effective

Internal Rating System

Consistent analytical approach to ratings and PDs – all asset classes

Transparency of methodology;

Visible audit trail;

Logical workflow, including sign-off and permissions;

Open architecture with a modular approach that is easily adaptable and scalable;

Data access aligned with roles and responsibilities; and

Centralised information storage


Building an internal rating system conceptual framework

2. Expected Loss Framework

  • Each prospective or existing loan facility must undergo three consecutive stages to determine expected loss.

Stage 1

Stage 3

Stage 2

Exposure at Default

Expected Loss

Rating (PD)

x

x

Loss Given

Default

=

Corporates

Banks

Insurance

Project Finance

SME

Data

Collateral

Haircut Policy

Seniority

Maturity etc


Building an internal rating system conceptual framework

3. Ratings and Pds

Across different asset classes

Low volume of data + High Exposure

RATING TEMPLATES ARE SUITABLE

Typical Loan Book

The methodologies used for assessment of creditworthiness of different asset classes should balance:

  • the volume and scope of data available, with

  • the relative exposure of the bank

High volume of data + Low Exposure

MODELS ARE SUITABLE


Building an internal rating system conceptual framework

Large corporates and

specialised lending

Characteristics of these sectors

  • Relatively large exposures to individual obligors

  • Qualitative factors can account for more than 50% of the risk of obligors

  • Scarce number of defaulting companies

  • Limited historical track record from many banks in some sectors

    Statistical models are NOT applicable in these sectors:

  • Models can severely underestimate the credit risk profile of obligors given the low proportion of historical defaults in the sectors.

  • Statistical models fail to include and ponder qualitative factors.

  • Models’ results can be highly volatile and with low predictive power.


Building an internal rating system conceptual framework

European Bank

Credit factors

Weights

Evaluation of Qualitative Factors

Large corporates and specialised lendingSample template – Insurance Companies


Building an internal rating system conceptual framework

Large corporates and specialised lendingSample template – Insurance Companies

Clear and consistent rating criteria


Building an internal rating system conceptual framework

European Bank

Evaluation of Quantitative Factors

Large corporates and specialised lendingSample template – Insurance Companies


Building an internal rating system conceptual framework

Large corporates and specialised lendingSample template – Insurance Companies

Quantitative Assessment Based on S&P’s Experience

Benchmarks are provided per sector and market


Building an internal rating system conceptual framework

Large corporates and specialised lendingSample template – Insurance Companies

Backtesting and Mapping to External Indicators of PD

Backtest model results versus S&P ratings or estimates

Compare results and

map the scales

Internal Rating Scale

S&P Scale

Use of external default data

Prepare for CBO/CLO

Satisfy board regarding the validity of an internal rating system

Identify areas of inconsistency in order to improve an internal ratings process


Building an internal rating system conceptual framework

Rating Assignment Horizon—Relationship with Business Cycle:point-in-time vs. through-the-cycle system

The time horizon of assessing the creditworthiness of borrowers in assigning ratings is also important. Two different approaches may be taken in considering the effect of the business cycle in assigning ratings. One is a point-in-time point-in-time system (PIT rating). In PIT rating, risks are evaluated based on the current condition of a firm regardless of the phase of the business cycle at the time of evaluation. The other is a through-the-cycle system (TTC rating). In TTC rating, risks are taken into account on the assumption that a firm is experiencing the bottom of the business cycle and is under

stress.


Pit rating vs ttc rating

PIT Rating vs TTC Rating


Building an internal rating system conceptual framework

4. Exposure and Facility Analysis

Exposure and Facility Analysis - Typically a corporate obligor will have a number of facilities with a bank, including secured and unsecured loans and overdraft facilities


5 lgd and definition of default

5. LGD and Definition of default

  • The definition of default is not the same in all countries, often bank behaviour is linked to national legal specificities

US

BASEL II

UK

FRANCE

GERMANY

ITALY

Bankruptcy

90 days credit obligation default

Debt restructuring

Credit obligation default


Building an internal rating system conceptual framework

Retail

Average

Oil & Gas

Healthcare

Television

Real Estate

Automotive

Comp. & Elec

Metals & Mining

Transportation

Printing & Pub.

Food & Beverage

Gaming & Hotel

Textile & Apparel

Services & Leasing

Building Materials

Retail Food & Drug

Manu. & Machinery

5. LGD – Loss Given Default -

LGD Behaviour in the US

  • Average Overall Recovery By Industry, some differences

Industries with 9+ Observations

70

60

50

Recovery (%)

40

30

20

10

0


Lgd behaviour

LGD Behaviour

LGD Behaviour by debt Structure and Industry

Overall - No Clear pattern!!

  • Need More data

  • Clear definitions

  • Need to pool data


Building an internal rating system conceptual framework

Loss Given Default

Loss Given Default: LGD information is scarce and complicated


Building an internal rating system conceptual framework

Expected Loss


Building an internal rating system conceptual framework

Concluding Comments

To build an internal rating system for Basel II you need:

  • Consistent rating methodology across asset classes

  • Use an expected loss framework

  • Data to calibrate Pd and LGD inputs

  • Logical and transparent workflow desk-top application

  • Appropriate back-testing and validation.

    Standard & Poor’s Risk Solutions


From pillar 1 to pillar 2

BIS II – IRB Advanced

From Pillar 1 to Pillar 2

From Expected Loss to Economic Capital

Business Processes

  • Risk Appetite

  • Capital Allocation

  • Active Portfolio Mgmt.

  • Mitigation Strategies

  • Risk Averse Pricing

  • RAPM & VaR limits

  • EcoCap Optimisation

Correlations

Portfolio Approach

  • Regulatory Capital Requirement

  • Risk-Adjusted Pricing

  • Provisioning Policies

  • Limits Based on EL

  • Early Warnings

Internal Rating Approach

  • Regulatory Capital Requirement

  • Risk-Adjusted Pricing

  • Provisioning Policies

  • Limits Based on EL

  • Early Warnings

Diversification

BIS II – IRB Foundation

BIS II – Standard Approach

  • Regulatory Capital Requirement

Inputs

  • External PD

  • Supervisory LGD

  • Supervisory EAD

  • Internal Estimate PD

  • Supervisory LGD

  • Supervisory EAD

  • Internal Estimate PD

  • Internal Estimate LGD

  • Internal estimate EAD

  • IRB Parameters

  • Macroeconomic Forecasts


Note1 expected loss el

Note1: Expected Loss (EL)

  • Expected Loss is the bank’s cost of doing business. Expected loss has to be provided for.

  • The Expected Loss (in currency amounts)

    EL = PD * EAD * LGD

    If expressed as a percentage figure of the EAD

    EL = PD * LGD.

  • The bank should also proactively incorporate an expected loss rate in the estimation of the total spread to be charged on the loan.

  • Expected loss is not a measure of risk as it is anticipated.


Note 2 unexpected loss ul

Note 2: Unexpected Loss (UL)

  • Regardless of how prudent a bank is in managing its day-to-day business activities, there are market conditions that can cause uncertainty in the amount of loss in portfolio value.

  • This uncertainty, or more appropriately the volatility of loss, is the unexpected loss. Unexpected losses are triggered by the occurrence of higher default rates as a result of unexpected credit migrations.


Note 3 el vs ul

Note 3:EL Vs UL


  • Login